dc.contributorMato Grosso State University
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T16:41:47Z
dc.date.available2018-12-11T16:41:47Z
dc.date.created2018-12-11T16:41:47Z
dc.date.issued2016-08-01
dc.identifierElectric Power Systems Research, v. 137, p. 41-50.
dc.identifier0378-7796
dc.identifierhttp://hdl.handle.net/11449/168559
dc.identifier10.1016/j.epsr.2016.03.040
dc.identifier2-s2.0-84962920038
dc.identifier2-s2.0-84962920038.pdf
dc.identifier1248956593236515
dc.identifier0000-0002-8846-2423
dc.description.abstractThis paper proposes a multiobjective model to solve the mathematical problem of optimizing reliability-centered maintenance planning of an electric power distribution system (EPDS). The main goal is to minimize the preventive maintenance costs while maximizing the index of reliability of the whole system. In the proposed model, the limits of the indices, such as SAIDI and SAIFI, are considered as constraints of the maintenance programs. The reliability indices of the EPDS components are evaluated and updated by a fuzzy inference system. A NSGA-II algorithm was proposed to solve the multiobjective model that provides an optimized Pareto frontier. The results obtained from applying the proposed methodology to a system with three feeders and 733 components are presented, showing its robustness and quality for maintenance planning in EPDS.
dc.languageeng
dc.relationElectric Power Systems Research
dc.relation1,048
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectFuzzy systems
dc.subjectNSGA-II
dc.subjectPower quality
dc.subjectPower system reliability
dc.subjectPreventive maintenance
dc.subjectReliability centered maintenance
dc.titleA new approach for reliability-centered maintenance programs in electric power distribution systems based on a multiobjective genetic algorithm
dc.typeOtros


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